8/14/2019 Rural financial institutions and microfinance
1/17
KINGSTON UNIVERSITY, LONDONSCHOOL OF ECONOMICS
Monetary Economics in Developing Countries(FE3178), 2009-2010
Lecture 3
Rural financial institutions and microfinance
Chapter 3, GSF
1
8/14/2019 Rural financial institutions and microfinance
2/17
Introduction
Banking soundness and financial depth, as well as rural- and
micro-credit markets, are significant in fostering economic
growth and development.
An interesting example illustrating the latter point is
Bangladeshs Grameen Bankfounded by Muhammad
Yunus, an economist who won the Nobel Peace Prize for his
path-breaking scheme.
That initiative embarked on overcoming the markets failure to
deliver much needed financial services and pioneered the
microcredit movement.
It originally aimed at providing small loans to seemingly risky
borrowers, and the experiment has resulted in remarkably high
loan recovery rates.
1
8/14/2019 Rural financial institutions and microfinance
3/17
Problems in underdeveloped markets
Observing high interest in developing countries rural areas vis-
-vis urban areas is not uncommon.
Differences between rates of interest charged within rural areas
can also diverge significantly.
For instance, Siamwalla et al (1990, WBER) investigate rural
credit markets in Thailand. They find that rural sector interest
rates were in the region of 60%. In contrast, those in the formal
sector fell within a range of 12-14%.
The microfinance literature draws from economic models on
asymmetric information and contract theory.
Information asymmetries
1
8/14/2019 Rural financial institutions and microfinance
4/17
The key elements for understanding microfinance are
borrowers lack of suitable collateral and the lack of reliable
information about those borrowers.
The first problem leads to moral hazard (involving
unobservable borrower behaviour), whereas the second is an
adverse selection problem (there is asymmetric information
between borrowers and lenders).
These problems are more generally known as market failures.
A way of overcoming those obstacles is peer-monitoring, which
implies thatjoint-liability by a group of borrowers somehow
helps in enforcing loan repayments.
Notably, joint-liability also involves peer-selection, and peer-
pressure if needed, in reaching and complying with a loan
agreement, respectively.
1
8/14/2019 Rural financial institutions and microfinance
5/17
2
8/14/2019 Rural financial institutions and microfinance
6/17
Stiglitz and Weisss (1981) credit rationing model
Stiglitz and Weiss (1981) make an important theoretical
contribution to the understanding ofcredit rationing in
markets with incomplete information.
Their model is particularly relevant for understanding the
problems affecting credit markets in developing countries.
Stiglitz and Weiss show that in equilibrium there may be credit
rationing, and thus under-investment, in credit markets with
adverse selection.
3
8/14/2019 Rural financial institutions and microfinance
7/17
The model
A bank and borrowers populate Stiglitz and Weisss model
economy.
Borrowers can invest in one project that lasts for a single period,
and they need funding equal to L for implementing it.
In securing that funding borrowers need to provide collateral C
amounting to less than L.
The gross payoffs from each project are distributed as F (R, ),
where R stands for the projects return and measures the
projects risk.
Thus successful projects can generate up to R, with higher
values implying more risk.
The bank and a borrower agree on a loan equal to L carrying a
corresponding interest rate r.
2
8/14/2019 Rural financial institutions and microfinance
8/17
A projects failure implies that returns from the project plus the
collateral are not enough to repay the amount borrowed.
What a bank ultimately gets back is a maximum amount
expected to be at least equal to the returns from the project plus
the collateral, or a maximum equal to the contractually agreed
sum L(1+r).
A critical feature of this model is that the interest rate acts as a
screening device. That is, lenders are able to sort out potential
borrowers based on the interest rate that they are willing to pay
for a given loan.
That is the case because a higher interest rate crowds-out less
risky borrowers. And that process also increases adverse
selection problems.
In turn
, the mean return on loans -defined as the product of
the interest rate and the repayment probability- decreases.
2
8/14/2019 Rural financial institutions and microfinance
9/17
As a result even though banks could benefit from charging a
higher interest rate they may be better-off not doing so because
increases in that variable triggers adverse selection problems.
So whether or not banks can actually benefit from a higher
interest rate will depend on the magnitude of two opposing
effects.
One effect arises directly from the higher interest rate and the
other indirectly from the adverse selection problems.
So, depending on the net outcome from these forces, beyond a
point
r
~
lenders may decide on rationing credit.
That behaviour gives the concave shape to the loans supply
curve (LS) in the Figure; i.e. a backward bending credit
supply for high levels of the interest rate.
2
8/14/2019 Rural financial institutions and microfinance
10/17
Note that LS is a function of the mean return on loans
, and not
of the interest rate.
In the Figure LD is the loan demand curve.
Further,
r~
, the bank-optimal interest rate, corresponds to the
highest possible
-that is B on the curve linking r and
- and
maps to the point at which Stiglitz and Weisss rationing
equilibrium occurs.
At that point there is a higher demand than supply for loans, an
excess demand for loans, which is equal to the distance between
LD and LS.
The market clearing interest rate r* corresponds to point A
where LD and LS. But Stiglitz and Weiss call attention to the fact
that r* is not an equilibrium interest rate.
3
8/14/2019 Rural financial institutions and microfinance
11/17
That is the case because the repayment probability and thus
drop sharply in the face of an increasing default risk resulting
from the higher interest rate. And that leads to a correspondingly
lower point on the LS curve linked to point A via the 45 degree
line in the north-west quadrant.
5
8/14/2019 Rural financial institutions and microfinance
12/17
Determination of the market equilibriumStiglitz and Weisss (1981) credit rationing model
1
Excess
demand
for
loans
SL
SL
DL
r
*r
8/14/2019 Rural financial institutions and microfinance
13/17
Overcoming adverse selection problems
Stiglitz and Weisss (1981)overcoming information
asymmetry is critical in fostering credit markets in developing
countries.
That is, solving adverse selection issues may induce lenders to
be more forthcoming in facilitating credit to borrowers without
collateral and traditional banking-customer characteristics.
But the actual presence of those adverse selection issues may
explain why in developing countries rural areas informal
finance, such as that expensively provided by moneylenders,
prevails.
Studies by Bell (1990), Siamwalla et al (1990), and Aleem
(1990), inter alia, actually show that these informal sources
of finance have been able to coexist with modern financial
institutions. And that is the case in the face of government
1
8/14/2019 Rural financial institutions and microfinance
14/17
initiatives aimed at fostering a move towards using the latter,
presumably more efficient, finance option.
In some cases traditional commercial banking institutions have
opted to provide services usually reserved to the informal sector.
What follows explains some theoretical approaches advanced
with the aim of better understanding key elements making-up
these fairly successful microfinance initiatives.
Particularly, explaining the roles of peer-monitoring, and of
group-lending and joint-liability, has generated an important
literature on the topic.
Peer-monitoring and group-lending
Stiglitzs (1990) is an early contribution to the literature on
peer-monitoring.
2
8/14/2019 Rural financial institutions and microfinance
15/17
Models based on peer-monitoring argue that -assuming group
members have better information about themselves than lenders,
say because they live close to each other- the technology is
likely to be cheaper than traditional finance monitoring.
Thusjoint-liability by a group of borrowers is expected to
somehow help in enforcing loan repayments. Notably, joint-
liability also involves peer-selection, and peer-pressure if
needed, in reaching and complying with a loan agreement,
respectively.
Varian (1990) also analyses peer-monitoring and joint-liability,
but he focuses on self-selection issues. Basically, in the model a
financial institution interviews a member of a given group. And
based on the outcome from that process the institution decides
on granting a credit or not. That, in turn, induces what can be
called a pre-screening exercise by group members before they
actually apply for credit. I.e., group members self-select each
other.
1
8/14/2019 Rural financial institutions and microfinance
16/17
Besley and Coate (1995) develop a strategic repayment game
with joint liability. They highlight the pros and cons implicit in
this type of scheme. Specifically, they show that successful
group members may have an incentive for repaying the loans of
the less successful ones. Yet there are cases in which the whole
group defaults whereas some members would have paid under
individual contracting.
Ghatak and Guinnane (1999) analyse moral hazard problems
in group-lending. In a model with moral hazard and monitoring
they find that if the social sanctions are effective enough or
monitoring costs are low enough, joint-liability lending will
improve repayment rates through peer-monitoring even when
monitoring is costly.
Ghatak (2000) and the related paper by Gangopadyay,
Ghatak, and Lensik (2005) reach the conclusion that under
joint liability contracts safe borrowers will cluster and form
homogeneous groups, while risky borrowers will be screened-
out.
2
8/14/2019 Rural financial institutions and microfinance
17/17
Ghatak also shows that under individual liability contracts
adverse selection may lead to underinvestment.
In contrast, joint-liability schemes can improve efficiency in
comparison with standard debt contracts.
3